From 0853eec4adfcbac05a4bec43f334234d17372906 Mon Sep 17 00:00:00 2001
From: Edward Hartnett <38856240+edwardhartnett@users.noreply.github.com>
Date: Thu, 10 Oct 2024 12:20:21 -0600
Subject: [PATCH] docs for chgres_cold2fv3.py (#519)

---
 docs/requirements.txt  |  3 +--
 ush/chgres_cold2fv3.py | 33 +++++++++++++++++++++++++++++++++
 2 files changed, 34 insertions(+), 2 deletions(-)

diff --git a/docs/requirements.txt b/docs/requirements.txt
index 2f34e05ab..817841744 100644
--- a/docs/requirements.txt
+++ b/docs/requirements.txt
@@ -2,7 +2,6 @@ sphinxcontrib-bibtex
 sphinx_rtd_theme
 docutils==0.16
 numpy
-xarray
-matplotlib
 netCDF4
+xarray
 matplotlib
diff --git a/ush/chgres_cold2fv3.py b/ush/chgres_cold2fv3.py
index b8de4011f..2dd7e10d1 100755
--- a/ush/chgres_cold2fv3.py
+++ b/ush/chgres_cold2fv3.py
@@ -1,3 +1,13 @@
+"""The purpose of this code is to convert a cold start file from
+chgres_cube into a FV3 warm start (restart) file, enabling data
+blending operators that require a warm start format. The code performs
+essential transformations, including wind rotation and vertical
+remapping of atmospheric scalars and winds, ensuring the cold start
+data aligns with the FV3 model's restart format. Reason: The global 6
+h background from chgres_cube is a cold start and must be converted to
+a warm start file to be able to blend with the 1 h EnKF restarts.
+
+"""
 import numpy as np
 from netCDF4 import Dataset
 import remap_dwinds
@@ -6,6 +16,29 @@
 import sys
 
 def nan_check(arr, name, check_id):
+    """NAN check function.
+
+    This function checks a given array for NaN (Not a Number) values,
+    counts the total number of NaNs, and prints their indices if any
+    are found. It helps identify problematic data in the array that
+    may disrupt further processing.
+
+    After all nan_checks are done, if there is at least one nan then
+    the code fails. I put a note right after the vertical remapping of
+    the wind that says "Perform a NaN check - sometimes will get NaNs
+    at this point". I don't think it should fail. I think it was more
+    of an issue in development and I kept the check there just to be
+    safe.
+
+    Parameters:
+    arr: numpy array to be checked for NaN values.
+    name: string used to label the array in the output for identification.
+    check_id: integer or string identifier to differentiate between multiple checks in the output.
+
+    Returns:
+    nan_count: integer representing the total number of NaN values found in the array.
+
+    """
     nan_count = 0
     nan_count = np.sum(np.isnan(arr))
     print(f"coldstartwinds({check_id}) nan_count({name}): {nan_count}")